The AI with cluster access found a sneaky shutdown bug in 10 minutes
Gave the AI kubectl access and it chased down a sneaky shutdown performance bug in 10 minutes, producing a spot-on diagnosis sent to developers.
A random mix from the whole library. Shuffle for a new set.
Gave the AI kubectl access and it chased down a sneaky shutdown performance bug in 10 minutes, producing a spot-on diagnosis sent to developers.
He made a tool for students that started as a simple quiz solver extension and grew slowly to just over $100 in monthly recurring revenue, with very little marketing. A month ago he reverse engineered Anki using AI, so anyone can bring their Anki deck and study it in his tool. He says that is the thing that worked.
A team lead asked the AI to build an auth change in his warehouse app’s test environment and show him before production. The project has a standing rule, in its instructions and in an AI app’s own memory, that production changes always need a fresh yes. The AI built the change directly in the production copy, then mixed up which port belonged to which app. Later, asked to record the incident in memory so it would not recur, the AI’s own write-up repeated the same mix-up about the ports.
A man who flips vintage items on eBay connected the AI to his store. The AI found 28 listings with views but no sales, worked out that eBay was really taking 16% in fees, and published a bundle of two vases that sold within a week.
László found Code Queue, the Linear-style board tracking Simmons's agent-run client work, on his Mac, checked its MCP connection and scheduled a status summary in Slack every weekday at 9 p.m. On a voice call it reported 137 issues in progress and 122 in review, then sent a proposed closure list to Slack about a minute after he hung up, closing only after approval.
Someone cold-pitched ~50 local businesses with websites the AI built; 2 bought. The website-flipping idea came from the AI itself; he just made the calls.
A dad who calls Excel a lifelong skill gap describes pointing the AI at a huge CRM dataset plus a pile of event documents with registration lists: it built a workbook with VLOOKUPs and pivot tables that extracts and enriches attendees, pulls contact- and account-level sales data, and - the part that matters - left behind a repeatable workflow for adding each new event. Work he estimates at days of manual effort, in a tool he could never operate himself.
An AI session started verification tests as background processes. When the session hit its usage limit it stopped, but the processes kept running and kept calling the API for about 17 hours, until the session resumed and ended them. Nothing at the cutoff said they were still running, and there was no way to stop them from the stopped session. The test loop had no cap on turns or calls. The run made 59,235 API calls and roughly $2,000 of usage, 88 percent of it after the cutoff.
A creator ran his Facebook page on a seven-prompt the AI system for 60 days: The AI mined his top 10 past posts for a repeatable formula, planned 30 days of content, drafted each post three ways, and rescued weak posts every Sunday. He reports 56.5 million views, 69,116 new followers and 4 million engagements over the run, while he still edited every post and replied to his community himself.
Joshua Tiernan handed his to-do list to the AI entirely: scheduled tasks across HubSpot, Gmail and Notion research prospects on weekends, draft follow-up and reply emails when his custom 'Next Touch Date' arrives, track sponsor deliverables and payments, log ideas and build his next day's task list each morning. Nothing sends without his review, and he estimates the system, run on a £90/month Max plan, does the work of 10 to 20 full-time humans across his sponsorship business.
Used GPT-6 to develop a new barcode scanner library, built a labelled real-world test suite, and published it for JS, Python and Rust.
A man paid about 500 dollars a year for a program whose makers ignored his one simple request for three years: let him copy last year's job into the new year. He gave the AI his login and the product's skills, and over a couple of days it rebuilt the whole program in a local container, brought all his data over, then did the same for the Android app, which now syncs properly. The rebuild cost about a tenth of one year's subscription.
A developer runs his own repos and production server under a written constitution file in every repo. Automated runs check production logs daily and file bug reports. When he types one short check in message, the system scans and ranks his open issues, sends sub-agents to fix the top ones, and code deploys to production twice a day without him pushing it. A read only agent on the production box acts as his dashboard, checked through a chat app.
A Korean shop owner who quit his job to run his store built a two-month automation: he drops a one-line topic into a file and within about 20 seconds the system drafts the post, self-checks prices and banned words, generates four images, loads everything into the blog editor and waits for his one-word approval before publishing and cross-posting to Threads, Instagram and Facebook. Image cost is about $0.16 per post against $200 a month of AI subscriptions.
Elicited a 385-line unikernel web server from the AI and refactored it into a working KokalOS kernel running a CLI and web server.
For a cleaning business, the AI manages contacts, drafts client messages, chases reviews and maintains the CRM, holding every outbound message for approval before it sends.
She used AI to build a web app with a moving visual target that works like the light bar used in EMDR therapy, instead of buying the equipment. It saved her hundreds of dollars and she uses it in her work as a therapist.
Mailing thousands of people brought hundreds of auto replies that nobody read. The AI scanned them read only, flagged who had left or changed roles, and updated Mailchimp, leaving a cleaner list and better deliverability.
Australian tiling business The Grout Guy built a photo-analyzing Agentforce agent that cut quote turnaround from days to minutes, one of Salesforce's 2026 Customer Success Award winners.
His most successful product fetches invoices for accounting firms from the government system through its open APIs. Tools like it charge per client per month; he sells his for a fixed price with lifetime access and support. He says he built a working copy of a well established system in a week by himself with AI, and it makes him a profit.
Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.